Experimentation to Evaluate the Benefits of Model Driven Development

Tesis por compendio[ES] El Desarrollo Dirigido por Modelos, MDD por sus siglas en inglés (Model Driven Development), es un enfoque de ingeniería del software que centra la creación y evolución de productos software en el modelado. Desde hace casi dos décadas, la comunidad científica ha descrito muchas de las ventajas de MDD frente a otros enfoques, sin embargo, su adopción en el entorno industrial es muy poco frecuente. Con el objetivo de entender por qué MDD no ha reemplazado otros enfoques de ingeniería software, he realizado una investigación empírica a través de tres experimentos controlados. Con el primer experimento pretendo aclarar si los beneficios de MDD frente al Desarrollo centrado en Código, CcD por sus siglas en inglés (Code Centric Development), son fieles a la realidad del desarrollo software actual. En el segundo experimento comparo la valoración que realizan los ingenieros de los modelos que utilizan, con su utilidad para ser utilizados en contextos MDD. En el tercer experimento analizo el desempeño de los profesionales software en tareas de mantenimiento en contextos MDD. Nuestros resultados confirman los beneficios de MDD frente a otros enfoques, pero también, que la intención de uso de MDD no alcanza valores máximos. Los sujetos subestiman el potencial de los modelos que desarrollan y utilizan en contextos MDD. El problema de adopción parece estar ligado a factores humanos, no a factores técnicos.[CA] El Desenvolupament Dirigit per Models, MDD (Model Driven Development), és un enfocament d'enginyeria del programari que centra la creació i evolució de productes programari en el modelatge. Des de fa quasi dues dècades, la comunitat científica ha descrit moltes dels avantatges de MDD enfront d'altres enfocaments, no obstant això, la seua adopció en l'entorn industrial és molt poc freqüent. Amb l'objectiu d'entendre per què MDD no ha reemplaçat altres enfocaments d'enginyeria programari, he realitzat una investigació empírica a través de tres experiments controlats. Amb el primer experiment pretenc aclarir si els beneficis de MDD enfront d'altres enfocaments, com el Desenvolupament centrat en Codi, CcD (Code Centric Development), són fidels a la realitat del desenvolupament programari actual. En el segon experiment compare la valoració que realitzen els enginyers dels models que utilitzen, amb la seua utilitat per a ser utilitzats en contextos MDD. En el tercer experiment analitze l'acompliment del professional programari en tasques de manteniment en contextos MDD. Els nostres resultats confirmen els beneficis de MDD enfront d'altres enfocaments, però també, que la intenció d'ús de MDD no aconsegueix valors màxims. Els subjectes subestimen el potencial dels models que desenvolupen i utilitzen en contextos MDD. El problema d'adopció sembla estar lligat a factors humans, no a factors tècnics.[EN] Model Driven Development (MDD) is a software engineering approach in which the code of a software product is generated and evolutionated from conceptual models that abstractly represents the system. For nearly two decades, the scientific community has described many of the advantages of MDD over other approaches. Despite the benefits of MDD, its use in real practical developments is merely anecdotal. To understand why MDD has not replaced other software engineering approaches, I have conducted an empirical investigation through three controlled experiments. The first experiment aims to clarify whether the benefits of MDD compared to code-centric development (CcD) match the reality of development in real environments. In the second experiment, I compare engineers' assessment of the models they develop with the usefulness of these models to be used in MDD contexts. In the third experiment, I analyze the performance of software professionals in maintenance tasks in MDD contexts. Our results confirm the benefits of MDD over other approaches; however, the intention to use MDD does not reach maximum values. Subjects underestimate the potential of the models they develop and use in MDD contexts. The adoption problem seems to be linked to human factors, not to technical factors.Domingo Montes, MÁ. (2022). Experimentation to Evaluate the Benefits of Model Driven Development [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185748Compendi

Traceability Links Recovery among Requirements and BPMN models

Tesis por compendio[EN] Throughout the pages of this document, I present the results of the research that was carried out in the context of my PhD studies. During the aforementioned research, I studied the process of Traceability Links Recovery between natural language requirements and industrial software models. More precisely, due to their popularity and extensive usage, I studied the process of Traceability Links Recovery between natural language requirements and Business Process Models, also known as BPMN models. In order to carry out the research, I focused my work on two main objectives: (1) the development of the Traceability Links Recovery techniques between natural language requirements and BPMN models, and (2) the validation and analysis of the results obtained by the developed techniques in industrial domain case studies. The results of the research have been redacted and published in forums, conferences, and journals specialized in the topics and context of the research. This thesis document introduces the topics, context, and objectives of the research, presents the academic publications that have been published as a result of the work, and then discusses the outcomes of the investigation.[ES] A través de las páginas de este documento, presento los resultados de la investigación realizada en el contexto de mis estudios de doctorado. Durante la investigación, he estudiado el proceso de Recuperación de Enlaces de Trazabilidad entre requisitos especificados en lenguaje natural y modelos de software industriales. Más concretamente, debido a su popularidad y uso extensivo, he estudiado el proceso de Recuperación de Enlaces de Trazabilidad entre requisitos especificados en lenguaje natural y Modelos de Procesos de Negocio, también conocidos como modelos BPMN. Para llevar a cabo esta investigación, mi trabajo se ha centrado en dos objetivos principales: (1) desarrollo de técnicas de Recuperación de Enlaces de Trazabilidad entre requisitos especificados en lenguaje natural y modelos BPMN, y (2) validación y análisis de los resultados obtenidos por las técnicas desarrolladas en casos de estudio de dominios industriales. Los resultados de la investigación han sido redactados y publicados en foros, conferencias y revistas especializadas en los temas y contexto de la investigación. Esta tesis introduce los temas, contexto y objetivos de la investigación, presenta las publicaciones académicas que han sido publicadas como resultado del trabajo, y expone los resultados de la investigación.[CA] A través de les pàgines d'aquest document, presente els resultats de la investigació realitzada en el context dels meus estudis de doctorat. Durant la investigació, he estudiat el procés de Recuperació d'Enllaços de Traçabilitat entre requisits especificats en llenguatge natural i models de programari industrials. Més concretament, a causa de la seua popularitat i ús extensiu, he estudiat el procés de Recuperació d'Enllaços de Traçabilitat entre requisits especificats en llenguatge natural i Models de Processos de Negoci, també coneguts com a models BPMN. Per a dur a terme aquesta investigació, el meu treball s'ha centrat en dos objectius principals: (1) desenvolupament de tècniques de Recuperació d'Enllaços de Traçabilitat entre requisits especificats en llenguatge natural i models BPMN, i (2) validació i anàlisi dels resultats obtinguts per les tècniques desenvolupades en casos d'estudi de dominis industrials. Els resultats de la investigació han sigut redactats i publicats en fòrums, conferències i revistes especialitzades en els temes i context de la investigació. Aquesta tesi introdueix els temes, context i objectius de la investigació, presenta les publicacions acadèmiques que han sigut publicades com a resultat del treball, i exposa els resultats de la investigació.Lapeña Martí, R. (2020). Traceability Links Recovery among Requirements and BPMN models [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/149391TESISCompendi

Traceability Link Recovery between Requirements and Models using an Evolutionary Algorithm Guided by a Learning to Rank Algorithm: Train control and management case

[EN] Traceability Link Recovery (TLR) has been a topic of interest for many years within the software engineering community. In recent years, TLR has been attracting more attention, becoming the subject of both fundamental and applied research. However, there still exists a large gap between the actual needs of industry on one hand and the solutions published through academic research on the other. In this work, we propose a novel approach, named Evolutionary Learning to Rank for Traceability Link Recovery (TLR-ELtoR). TLR-ELtoR recovers traceability links between a requirement and a model through the combination of evolutionary computation and machine learning techniques, generating as a result a ranking of model fragments that can realize the requirement. TLR-ELtoR was evaluated in a real-world case study in the railway domain, comparing its outcomes with five TLR approaches (Information Retrieval, Linguistic Rule-based, Feedforward Neural Network, Recurrent Neural Network, and Learning to Rank). The results show that TLR-ELtoR achieved the best results for most performance indicators, providing a mean precision value of 59.91%, a recall value of 78.95%, a combined F-measure of 62.50%, and a MCC value of 0.64. The statistical analysis of the results assesses the magnitude of the improvement, and the discussion presents why TLR-ELtoR achieves better results than the baselines.This work has been developed with the financial support of the Spanish State Research Agency and the Generalitat Valenciana under the projects DataME TIN2016-80811-P, ALPS RT12018-096411-B-100, ACIF/2018/171 and PROMETEO/2018/176, and co-financed with ERDF.Marcén, AC.; Lapeña, R.; Pastor López, O.; Cetina, C. (2020). 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